Previous researchers have made impressive strides in develo** algorithms and solution
methodologies to address multi-objective optimization (MOO) problems in industrial …

This paper proposes an intelligent self-organized algorithm (ISOA) to solve a cooperative
search-attack mission planning problem for multiple unmanned aerial vehicles (multi-UAV) …

Diagnosis of Parkinson's disease at its early stage is important in proper treatment of the
patients so they can lead productive lives for as long as possible. Although many techniques …

Conventional multiobjective optimization algorithms (MOEAs) with or without preferences
are successful in solving multi-and many-objective optimization problems. However, a …

A task allocation problem for heterogeneous unmanned aerial vehicles (UAVs) in the
presence of environment uncertainty is studied in this paper. Generally, the process of …

Optimization of crop structure is an efficient way to reduce greenhouse gas (GHGs) from
agriculture production. However, carbon footprint have rarely been incorporated into …

The hardly dominated boundary (HDB) is commonly observed in multi-objective optimization
problems (HDBMOPs). However, there are only a few benchmark problems related to HDB …

In preference-based multi-objective optimization, knee solutions are termed as the implicit
preferred promising solution, particularly when users have trouble in articulating any …

In the last two decades, the non-dominated sorting genetic algorithm II (NSGA-II) has been
the most widely-used evolutionary multi-objective optimization (EMO) algorithm. However …

Unmanned Aerial Vehicle (UAVs) have become very popular in the last decade due to some
advantages such as strong terrain adaptation, low cost, zero casualties, and so on. One of …